Every claim has a past. Nodal already knows it.

Nodal provides P&C claims triage in workers’ compensation, general liability, and commercial auto. The models are tailored to your book and adapt to the regulatory and litigation environment of the states where you operate.

Unstructured data is information that is not organized in a pre-set data model or database, such as text-heavy files. In the context of claims triage, this includes adjuster notes, medical reports, and police records. Nodal uses natural language processing (NLP) and AI to extract risk signals, like attorney involvement or injury severity, that are often buried in these notes, allowing for more accurate scoring than traditional field-based models.

By automating the initial review process, Nodal delivers an average adjuster productivity lift of 15–25%. Instead of manually hunting for high-risk files, adjusters receive daily risk scores and next-best-action recommendations. This allows your team to focus their expertise on the most complex claims that require immediate intervention.

Our clients typically see a 5–10% reduction in total claim costs and an 8–10x average increase in ROI. By identifying 85% of high-cost claims within the first 10 days, Nodal enables early intervention before medical costs escalate or litigation risks increase.

Unlike rip-and-replace software, Nodal is designed to deploy alongside your existing claims management system or RMIS. Most carriers, TPAs, risk pools, and self-insured employers are live and seeing results within six to eight weeks, ensuring a rapid return on investment without disrupting current workflows.

Building in-house means your models are only as good as your own claims history, and that history has blind spots: it can’t tell you what care should cost outside your book, and it normalizes the patterns already baked into your data. It also means standing up data science, NLP, and actuarial capabilities you’d have to maintain as your book changes. Nodal is built by Milliman, the actuarial firm insurers already trust to price risk, and it’s tuned to your data while validating against outside benchmarks a single book can’t generate on its own. You get a model calibrated to your environment without carrying the cost of building and maintaining one, and you’re live in six to eight weeks instead of quarters.

Doing nothing has a price that doesn’t show up on an invoice. Ten percent of claims drive the majority of cost, and they don’t look different at intake, so every quarter without early identification is another set of claims that escalate before anyone sees them coming. The window to change a claim’s trajectory is widest at the start and closes fast; by the time severity or litigation is obvious, the intervention that would have mattered is no longer available. Waiting doesn’t hold the line, it lets the costly claims keep slipping through while adjuster capacity stays stretched across files that don’t need the attention.